Former Food Products Safety Evaluation: Computer Vision as an Innovative Approach for the Packaging Remnants Detection

Former food products (FFPs) represent a way by which leftovers from the food industry (e.g., biscuits, bread, breakfast cereals, chocolate bars, pasta, savoury snacks, and sweets) are converted into ingredients for the feed industry, thereby keeping food losses in the food chain. FFPs represent an a...

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Veröffentlicht in:Journal of food quality 2017-01, Vol.2017 (2017), p.1-6
Hauptverfasser: Pinotti, Luciano, Chiofalo, Vincenzo, Leone, Francesco, Rebucci, Raffaella, Fusi, Eleonora, Giromini, Carlotta, Di Rosa, Ambra Rita, Ottoboni, Matteo, Tretola, Marco, Dell’Orto, Vittorio
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Sprache:eng
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Zusammenfassung:Former food products (FFPs) represent a way by which leftovers from the food industry (e.g., biscuits, bread, breakfast cereals, chocolate bars, pasta, savoury snacks, and sweets) are converted into ingredients for the feed industry, thereby keeping food losses in the food chain. FFPs represent an alternative source of nutrients for animal feeding. However, beyond their nutritional value, the use of FFPs in animal feeding implies also safety issues, such as those related to the presence of packaging remnants. These contaminants might reside in FFP during food processing (e.g., collection, unpacking, mixing, grinding, and drying). Nowadays, artificial senses are widely used for the detection of foreign material in food and all of them involve computer vision. Computer vision technique provides detailed pixel-based characterizations of colours spectrum of food products, suitable for quality evaluation. The application of computer vision for a rapid qualitative screening of FFP’s safety features, in particular for the detection of packaging remnants, has been recently tested. This paper presents the basic principles, the advantages, and disadvantages of the computer vision method with an evaluation of its potential in the detection of packaging remnants in FFP.
ISSN:0146-9428
1745-4557
DOI:10.1155/2017/1064580